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Business Intelligence-The Next Frontier in Enterprise Productivity
Manoj Semel
Wednesday, June 12, 2019
Right after 9/11, a major retailer identifies a surge in demand for the American flag and the ability to meet the demand and catch the wave, ahead of other retailers.

A major Telco consolidates vendor information from several purchasing and financial systems and identifies a single supplier that has been entered using 17 different names. The telco recognizes that they make significant purchase from this supplier, and is able to negotiate more favorable contracts.

Read More: Read More: Top Business Intelligence companies in India

The common theme in the above cases Intelligence was gathered over vast amount of data from disparate IT systems running within a enterprise to identify actionable patterns; to improve processes; sales, purchase and target marketing. Welcome to the world of Business Intelligence.

The last decade saw the emergence of packaged applications that helped customers streamline their business processes. Enterprise Resource Planning software packages from SAP, Oracle, PeopleSoft and Baan were deployed to run customers financial, purchasing and other back office activities. Customer Relationship Management packages from Siebel & Vantive were used to manage marketing, sales and customer support. Supply Chain Management systems from I2 and Manugistics were set up to streamline interaction between an enterprise and its suppliers and to optimize the pipeline.

Each of these systems allows companies to streamline departmental operations such as finance, purchasing and sales. Many organizations support some form of homegrown applications and processes. But it was the software companies that implemented standard processes and best practices into their package. This allows standardization of operations and reaps rewards of efficient processes.

Once the ERP and CRM systems were stabilized and the operational efficiency squeezed out; organizations explored other avenues to get greater insight into their business drivers and to improve their Critical Success Factors.
CSF can be defined as increased sales, increased profitability, higher response to promotions, higher customer satisfaction, and lesser customer churn. To achieve CSF, complex issues need to be identified; the most profitable customers may not be necessarily same as biggest customers. The most profitable products, may not be same as best selling product; the best vendors, not necessarily the one with lowest price.

Calculating product profitability can be very complex process. In addition to the initial sale price of a product other factors like cost of promotions, cost of customer support and handling returns should be considered. Organizations have multiple sales channels such as stores, telemarketing, Web; requiring extra consideration of each channel. Further, computation of the costs can be complex since sale price is per item where some costs are at different levels such as cost of entire promotion is known but is not broken per product. Thus promotion cost need to be distributed across items and sale that happened during or immediately after promotion.

Must Read: Is Business Intelligence (BI) using Analytics the Edge which helps CIO move closer to Business?

- Great Insights by Lalit Popli, Head of Information Technology, ICICI Prudential AMC

Another example of complexity behind a common question is: Who are the best suppliers for the products? The answer is not necessarily the one who has the lowest price. Account payment term, quality of the products supplied, percentage of on-time shipments, capacity to handle sudden changes in demand and ability to synchronize its supply chain to order systems should also be considered.

Questions like these are vital for organizations to succeed or even just to survive in today's global competition but cannot be answered by using data from just one operational system like CRM. This is where the Business Intelligence systems come into play.

A BI system typically consists of the following components:

l A Data Warehouse and/or data marts. Data warehouses are typically implemented using relational databases from Oracle, IBM, Microsoft, and Teradata. Data marts can be implemented using relational databases or multi-dimensional cubes (e.g. Cognos, Hyperian etc.)

l Tools to Extract, Transform and Load data from operational systems into DW. ETL tools are available from pure-play companies like Informatica, Ascential and Ab-initio but are also available from database vendors like Microsoft and Oracle.

l Tools for analysis and reporting using data in the DW or data marts. Business Objects, Cognos, Microstrategy, Microsoft and Oracle provide such tools

l Tools for Knowledge Discovery and pattern finding using data mining. Strong players in this segment are SAS Institute and SPSS.

l Applications for sophisticated forecasting and planning based on the integrated data in the DW, also called analytical applications. Hyperian, SAS, Oracle and SAP offer a suite of analytical applications.

Data from one or more operational system(s) like ERP or CRM system is brought into a DW using ETL tool. The data is cleansed, invalid values identified and rectified. When the data comes from multiple systems, it is also conformed and merged into a single identity.

This conformation process presents an accurate picture; the data can also be enriched using third party data. While dealing with seemingly different organizations of one global corporation, additional information from a third party like Dunn and Bradstreet, allows the user to deduce that multiple organizations are indeed part of one company. In addition, the DW is designed to have far more historical data ranging between three and five years than the systems that need to retain data only for a year or so.

The DW thus has clean, integrated and enriched data from multiple systems like finance, marketing, sales, support, procurement and manufacturing to name a few; and provides a solid foundation for a complete 360-degree view of a company's key assets and processes like customers, products, regions, channels, orders and suppliers.

Once the DW is designed and populated, one or more BI tools are used to present the information in business friendly terms to the users. Unlike operational systems whose users tend to be the people running daily operations such as order entry or customer support representative. The real power of BI solutions is in the flexibility and visual nature of information it presents. Executives can quickly get a high understanding using presentation mechanism like Scorecards and Dashboards that present information using a series of dials and gauges. They can drill-down into problematic areas with just a few clicks and zoom into a detailed information section about a problem.

Business analysts use other BI presentation tools to do a slice-and-dice of data to obtain different perspectives of the same facts and a what-if analysis. Line managers can benefit from periodic reports generated using integrated data in the DW.

The BI system thus has a complete view of an organizations business and is a unique asset where organizations can not only analyze the past events but also extrapolate to plan the future. If ERP is about how to capture, process and order, BI is about what products to sell, how to price and promote them. If, Sales Force Automation is about how to capture customer order life cycle, BI is about which customers to target and retain. BI is thus a logical extension to the operational systems and adds to the ROI the organizations invested in implementing the operational systems like ERP and CRM. Organizations have become aware of the unique value the BI initiative brings and high adaptation rate of BI systems is happening in last few years.

In summary, if ERP was about Doing things right, BI is about ?Doing right things.?

Manoj Samel is an Enterprise Warehouse & Analytics Architect at Oracle Corp. He can be reached at manoj_samel@yahoo.com
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